Kafene is revolutionizing the lease-to-own space. We're the point-of-sale powerhouse making flexible lease-to-own accessible to everyone—prime and non-prime customers alike. Our secret weapon? Cutting-edge AI and machine learning that analyzes 20,000+ data inputs in real-time, empowering retailers across furniture, appliances, electronics, tires, and durable goods to say "yes" to more customers.
The numbers tell our story: over $400 million in sales and counting. But we're just getting started.
Our 150-person team spans NYC headquarters, Wilmington, and remote talent across the nation—all united by a culture that thrives on collaboration, innovation, and genuine support. We don't just talk about great workplace culture; we deliver it. That's why Built In named us a Startup to Watch and Forbes recognized us as one of the Best Startup Employers.
Ready to be part of the fintech revolution? Join us.
The Data Engineering Team is the driving force behind our data-driven culture at Kafene. We partner closely with Kafene’s Risk, Technology, Sales, and Product teams to understand the various business processes that make up our users' day-to-day responsibilities and help to identify areas of improvement.
We are seeking a Business Intelligence Engineer to join our growing team. This role will be responsible for helping provide technical experience in extracting, integrating, and analyzing critical data that helps to identify complex business challenges, identify opportunities, and assist in the designing of solutions to improve our operations. The ideal candidate is extremely collaborative with excellent communication skills and is relentless in their pursuit of project completion.
Key Responsibilities:
Apply technical expertise to independently execute the extraction, integration, and analysis of critical data
Identify complex business challenges, uncover opportunities, and design solutions that improve business operations
Develop, maintain, and enhance internal data warehouses and datamarts to support scalable reporting and analytics
Build and optimize ETL processes and CI/CD pipelines across multiple tools and technologies
Analyze and investigate data defects, partnering with stakeholders to determine root causes and implement corrective actions
Collaborate with Tech, Risk, RevOps, and Marketing teams to execute cross-functional initiatives and support business objectives
Core Skills and Qualification